{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,27]],"date-time":"2025-06-27T10:41:08Z","timestamp":1751020868361,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":35,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,3,25]],"date-time":"2022-03-25T00:00:00Z","timestamp":1648166400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Beijing Natural Science Foundation","award":["Grant No.3212009"],"award-info":[{"award-number":["Grant No.3212009"]}]},{"name":"National Natural Science Foundation of China","award":["Grant No.52175019, 62176025"],"award-info":[{"award-number":["Grant No.52175019, 62176025"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,3,25]]},"DOI":"10.1145\/3529446.3529453","type":"proceedings-article","created":{"date-parts":[[2022,7,15]],"date-time":"2022-07-15T22:14:02Z","timestamp":1657923242000},"page":"37-43","source":"Crossref","is-referenced-by-count":1,"title":["Hierarchical Iris Image Super Resolution based on Wavelet Transform"],"prefix":"10.1145","author":[{"given":"YUFENG","family":"XIA","sequence":"first","affiliation":[{"name":"Automation School, Beijing University of Posts and Telecommunications, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"PEIPEI","family":"LI","sequence":"additional","affiliation":[{"name":"Artificial Intelligence School, Beijing University of Posts and Telecommunications, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"JIA","family":"WANG","sequence":"additional","affiliation":[{"name":"Artificial Intelligence School, Beijing University of Posts and Telecommunications, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"ZHILI","family":"ZHANG","sequence":"additional","affiliation":[{"name":"Computer Science School, Beijing University of Posts and Telecommunications, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"DUANLING","family":"LI","sequence":"additional","affiliation":[{"name":"Automation School, Beijing University of Posts and Telecommunications, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"ZHAOFENG","family":"HE","sequence":"additional","affiliation":[{"name":"Artificial Intelligence School, Beijing University of Posts and Telecommunications, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,7,15]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"crossref","unstructured":"Dong C.; Loy C. C.; He K.; and Tang X. 2015. Image super-resolution using deep convolutional networks. IEEE transactions on pattern analysis and machine intelligence 38(2): 295\u2013307.  Dong C.; Loy C. C.; He K.; and Tang X. 2015. Image super-resolution using deep convolutional networks. IEEE transactions on pattern analysis and machine intelligence 38(2): 295\u2013307.","DOI":"10.1109\/TPAMI.2015.2439281"},{"volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Kim J.","key":"e_1_3_2_1_2_1","unstructured":"Kim , J. ; Lee , J. K. ; and Lee , K. M . 2016. Accurate Image Super-Resolution Using Very Deep Convolutional Networks . In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Kim, J.; Lee, J. K.; and Lee, K. M. 2016. Accurate Image Super-Resolution Using Very Deep Convolutional Networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"e_1_3_2_1_3_1","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.","author":"Lim B.","year":"2017","unstructured":"Lim , B. ; Son , S. ; Kim , H. ; Nah , S. ; and Mu Lee , K. 2017 . Enhanced Deep Residual Networks for Single Image Super-Resolution . In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. Lim, B.; Son, S.; Kim, H.; Nah, S.; and Mu Lee, K. 2017. Enhanced Deep Residual Networks for Single Image Super-Resolution. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops."},{"volume-title":"Proceedings of the European conference on computer vision (ECCV), 286\u2013301","author":"Zhang Y.","key":"e_1_3_2_1_4_1","unstructured":"Zhang , Y. ; Li , K. ; Li , K. ; Wang , L. ; Zhong , B. ; and Fu , Y . 2018b. Image super-resolution using very deep residual channel attention networks . In Proceedings of the European conference on computer vision (ECCV), 286\u2013301 . Zhang, Y.; Li, K.; Li, K.; Wang, L.; Zhong, B.; and Fu, Y. 2018b. Image super-resolution using very deep residual channel attention networks. In Proceedings of the European conference on computer vision (ECCV), 286\u2013301."},{"volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Dai T.","key":"e_1_3_2_1_5_1","unstructured":"Dai , T. ; Cai , J. ; Zhang , Y. ; Xia , S.-T. ; and Zhang , L . 2019. Second-Order Attention Network for Single Image Super-Resolution . In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Dai, T.; Cai, J.; Zhang, Y.; Xia, S.-T.; and Zhang, L. 2019. Second-Order Attention Network for Single Image Super-Resolution. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"e_1_3_2_1_6_1","article-title":"Densely residual Laplacian super-resolution","author":"Anwar S.","year":"2020","unstructured":"Anwar , S. ; and Barnes , N. 2020 . Densely residual Laplacian super-resolution . IEEE Transactions on Pattern Analysis and Machine Intelligence. Anwar, S.; and Barnes, N. 2020. Densely residual Laplacian super-resolution. IEEE Transactions on Pattern Analysis and Machine Intelligence.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence."},{"volume-title":"Proceedings of the European conference on computer vision (ECCV), 191\u2013207","author":"Niu B.","key":"e_1_3_2_1_7_1","unstructured":"Niu , B. ; Wen , W. ; Ren , W. ; Zhang , X. ; Yang , L. ; Wang , S. ; Zhang , K. ; Cao , X. ; and Shen , H . 2020. Single image super-resolution via a holistic attention network . In Proceedings of the European conference on computer vision (ECCV), 191\u2013207 . Springer. Niu, B.; Wen, W.; Ren, W.; Zhang, X.; Yang, L.; Wang, S.; Zhang, K.; Cao, X.; and Shen, H. 2020. Single image super-resolution via a holistic attention network. In Proceedings of the European conference on computer vision (ECCV), 191\u2013207. Springer."},{"volume-title":"Proceedings of the IEEE International Conference on Computer Vision (ICCV), 1689\u20131697","author":"Huang H.","key":"e_1_3_2_1_8_1","unstructured":"Huang , H. ; He , R. ; Sun , Z. ; and Tan , T . 2017. Wavelet-srnet: A wavelet-based cnn for multi-scale face super resolution . In Proceedings of the IEEE International Conference on Computer Vision (ICCV), 1689\u20131697 . Huang, H.; He, R.; Sun, Z.; and Tan, T. 2017. Wavelet-srnet: A wavelet-based cnn for multi-scale face super resolution. In Proceedings of the IEEE International Conference on Computer Vision (ICCV), 1689\u20131697."},{"volume-title":"2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS), 1\u20138. IEEE.","author":"Alonso-Fernandez F.","key":"e_1_3_2_1_9_1","unstructured":"Alonso-Fernandez , F. ; Farrugia , R. A. ; and Bigun , J . 2016. Very low-resolution iris recognition via Eigen-patch super-resolution and matcher fusion . In 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS), 1\u20138. IEEE. Alonso-Fernandez, F.; Farrugia, R. A.; and Bigun, J. 2016. Very low-resolution iris recognition via Eigen-patch super-resolution and matcher fusion. In 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS), 1\u20138. IEEE."},{"volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 153\u2013161","author":"Alonso-Fernandez F.","key":"e_1_3_2_1_10_1","unstructured":"Alonso-Fernandez , F. ; Farrugia , R. A. ; and Bigun , J . 2017. Iris super-resolution using iterative neighbor embedding . In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 153\u2013161 . Alonso-Fernandez, F.; Farrugia, R. A.; and Bigun, J. 2017. Iris super-resolution using iterative neighbor embedding. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 153\u2013161."},{"volume-title":"2015 IEEE International Conference on Image Processing (ICIP), 3856\u20133860","author":"Aljadaany R.","key":"e_1_3_2_1_11_1","unstructured":"Aljadaany , R. ; Luu , K. ; Venugopalan , S. ; and Savvides , M . 2015. Iris super-resolution via nonparametric over-complete dictionary learning . In 2015 IEEE International Conference on Image Processing (ICIP), 3856\u20133860 . IEEE. Aljadaany, R.; Luu, K.; Venugopalan, S.; and Savvides, M. 2015. Iris super-resolution via nonparametric over-complete dictionary learning. In 2015 IEEE International Conference on Image Processing (ICIP), 3856\u20133860. IEEE."},{"volume-title":"Chinese Conference on Biometric Recognition, 399\u2013406","author":"Zhang Q.","key":"e_1_3_2_1_12_1","unstructured":"Zhang , Q. ; Li , H. ; He , Z. ; and Sun , Z . 2016. Image super-resolution for mobile iris recognition . In Chinese Conference on Biometric Recognition, 399\u2013406 . Springer Zhang, Q.; Li, H.; He, Z.; and Sun, Z. 2016. Image super-resolution for mobile iris recognition. In Chinese Conference on Biometric Recognition, 399\u2013406. Springer"},{"volume-title":"2017 25th European Signal Processing Conference (EUSIPCO), 2176\u20132180","author":"Ribeiro E.","key":"e_1_3_2_1_13_1","unstructured":"Ribeiro , E. ; Uhl , A. ; Alonso-Fernandez , F. ; and Farrugia , R. A . 2017. Exploring deep learning image super-resolution for iris recognition . In 2017 25th European Signal Processing Conference (EUSIPCO), 2176\u20132180 . IEEE. Ribeiro, E.; Uhl, A.; Alonso-Fernandez, F.; and Farrugia, R. A.2017. Exploring deep learning image super-resolution for iris recognition. In 2017 25th European Signal Processing Conference (EUSIPCO), 2176\u20132180. IEEE."},{"volume-title":"2017 International Conference of the Biometrics Special Interest Group (BIOSIG), 1\u20135. IEEE.","author":"Ribeiro E.","key":"e_1_3_2_1_14_1","unstructured":"Ribeiro , E. ; and Uhl , A . 2017. Exploring texture transfer learning via convolutional neural networks for iris super resolution . In 2017 International Conference of the Biometrics Special Interest Group (BIOSIG), 1\u20135. IEEE. Ribeiro, E.; and Uhl, A. 2017. Exploring texture transfer learning via convolutional neural networks for iris super resolution. In 2017 International Conference of the Biometrics Special Interest Group (BIOSIG), 1\u20135. IEEE."},{"volume-title":"2019 International Conference on Biometrics (ICB), 1\u20138. IEEE.","author":"Guo Y.","key":"e_1_3_2_1_15_1","unstructured":"Guo , Y. ; Wang , Q. ; Huang , H. ; Zheng , X. ; and He , Z . 2019. Adversarial iris super resolution . In 2019 International Conference on Biometrics (ICB), 1\u20138. IEEE. Guo, Y.; Wang, Q.; Huang, H.; Zheng, X.; and He, Z. 2019. Adversarial iris super resolution. In 2019 International Conference on Biometrics (ICB), 1\u20138. IEEE."},{"key":"e_1_3_2_1_16_1","volume-title":"Iris Image Super Resolution Based on GANs with Adversarial Triplets. In Chinese Conference on Biometric Recognition,346\u2013353","author":"Wang X.","year":"2019","unstructured":"Wang , X. ; Zhang , H. ; Liu , J. ; Xiao , L. ; He , Z. ; Liu , L. ; and Duan , P. 2019 . Iris Image Super Resolution Based on GANs with Adversarial Triplets. In Chinese Conference on Biometric Recognition,346\u2013353 . Springer. Wang, X.; Zhang, H.; Liu, J.; Xiao, L.; He, Z.; Liu, L.; and Duan ,P. 2019. Iris Image Super Resolution Based on GANs with Adversarial Triplets. In Chinese Conference on Biometric Recognition,346\u2013353. Springer."},{"key":"e_1_3_2_1_17_1","unstructured":"Vaswani A.; Shazeer N.; Parmar N.; Uszkoreit J.; Jones L.;Gomez A. N.; Kaiser \u0141.; and Polosukhin I. 2017. Attention is all you need. In Advances in neural information processing systems 5998\u20136008.  Vaswani A.; Shazeer N.; Parmar N.; Uszkoreit J.; Jones L.;Gomez A. N.; Kaiser \u0141.; and Polosukhin I. 2017. Attention is all you need. In Advances in neural information processing systems 5998\u20136008."},{"volume-title":"International Conference on Machine Learning, 4055\u20134064","author":"Parmar N.","key":"e_1_3_2_1_18_1","unstructured":"Parmar , N. ; Vaswani , A. ; Uszkoreit , J. ; Kaiser , L. ; Shazeer , N. ; Ku , A. ; and Tran , D . 2018. Image transformer . In International Conference on Machine Learning, 4055\u20134064 . PMLR. Parmar, N.; Vaswani, A.; Uszkoreit, J.; Kaiser, L.; Shazeer, N.; Ku,A.; and Tran, D. 2018. Image transformer. In International Conference on Machine Learning, 4055\u20134064. PMLR."},{"key":"e_1_3_2_1_19_1","unstructured":"Dosovitskiy A.; Beyer L.; Kolesnikov A.; Weissenborn D.;Zhai X.; Unterthiner T.; Dehghani M.; Minderer M.; Heigold G.; Gelly S.; 2020. An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929.  Dosovitskiy A.; Beyer L.; Kolesnikov A.; Weissenborn D.;Zhai X.; Unterthiner T.; Dehghani M.; Minderer M.; Heigold G.; Gelly S.; 2020. An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929."},{"volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 5791\u20135800","author":"Yang F.","key":"e_1_3_2_1_20_1","unstructured":"Yang , F. ; Yang , H. ; Fu , J. ; Lu , H. ; and Guo , B . 2020. Learning texture transformer network for image super-resolution . In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 5791\u20135800 . Yang, F.; Yang, H.; Fu, J.; Lu, H.; and Guo, B. 2020. Learning texture transformer network for image super-resolution. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 5791\u20135800."},{"volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 12299\u201312310","author":"Chen H.","key":"e_1_3_2_1_21_1","unstructured":"Chen , H. ; Wang , Y. ; Guo , T. ; Xu , C. ; Deng , Y. ; Liu , Z. ; Ma , S. ; Xu , C. ; Xu , C. ; and Gao , W . 2021. Pre-trained image processing transformer . In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 12299\u201312310 . Chen, H.; Wang, Y.; Guo, T.; Xu, C.; Deng, Y.; Liu, Z.; Ma, S.; Xu, C.; Xu, C.; and Gao, W. 2021. Pre-trained image processing transformer. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 12299\u201312310."},{"key":"e_1_3_2_1_22_1","volume-title":"Cvt: Introducing convolutions to vision transformers. arXiv preprint arXiv:2103.15808.","author":"Wu H.","year":"2021","unstructured":"Wu , H. ; Xiao , B. ; Codella , N. ; Liu , M. ; Dai , X. ; Yuan , L. ; and Zhang , L . 2021 . Cvt: Introducing convolutions to vision transformers. arXiv preprint arXiv:2103.15808. Wu, H.; Xiao, B.; Codella, N.; Liu, M.; Dai, X.; Yuan, L.; and Zhang, L. 2021. Cvt: Introducing convolutions to vision transformers. arXiv preprint arXiv:2103.15808."},{"key":"e_1_3_2_1_23_1","volume-title":"Conformer: Local Features Coupling Global Representations for Visual Recognition. arXiv preprint arXiv:2105.03889.","author":"Peng Z.","year":"2021","unstructured":"Peng , Z. ; Huang , W. ; Gu , S. ; Xie , L. ; Wang , Y. ; Jiao , J. ; and Ye , Q . 2021 . Conformer: Local Features Coupling Global Representations for Visual Recognition. arXiv preprint arXiv:2105.03889. Peng, Z.; Huang, W.; Gu, S.; Xie, L.; Wang, Y.; Jiao, J.; and Ye, Q. 2021. Conformer: Local Features Coupling Global Representations for Visual Recognition. arXiv preprint arXiv:2105.03889."},{"volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR), 2472\u20132481","author":"Zhang Y.","key":"e_1_3_2_1_24_1","unstructured":"Zhang , Y. ; Tian , Y. ; Kong , Y. ; Zhong , B. ; and Fu , Y . 2018c. Residual dense network for image super-resolution . In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR), 2472\u20132481 . Zhang, Y.; Tian, Y.; Kong, Y.; Zhong, B.; and Fu, Y. 2018c. Residual dense network for image super-resolution. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR), 2472\u20132481."},{"volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","author":"Shi W.","key":"e_1_3_2_1_25_1","unstructured":"Shi , W. ; Caballero , J. ; Huszar , F. ; Totz , J. ; Aitken , A. P. ; Bishop , \u00b4 R. ; Rueckert , D. ; and Wang , Z . 2016. Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network . In Proceedings of the IEEE conference on computer vision and pattern recognition , 1874\u20131883. Shi, W.; Caballero, J.; Huszar, F.; Totz, J.; Aitken, A. P.; Bishop, \u00b4R.; Rueckert, D.; and Wang, Z. 2016. Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network. In Proceedings of the IEEE conference on computer vision and pattern recognition, 1874\u20131883."},{"volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition, 6848\u20136856","author":"Zhang X.","key":"e_1_3_2_1_26_1","unstructured":"Zhang , X. ; Zhou , X. ; Lin , M. ; and Sun , J . 2018a. Shufflenet: An extremely efficient convolutional neural network for mobile devices . In Proceedings of the IEEE conference on computer vision and pattern recognition, 6848\u20136856 . Zhang, X.; Zhou, X.; Lin, M.; and Sun, J. 2018a. Shufflenet: An extremely efficient convolutional neural network for mobile devices. In Proceedings of the IEEE conference on computer vision and pattern recognition, 6848\u20136856."},{"key":"e_1_3_2_1_27_1","unstructured":"Hu J.; Shen L.; Albanie S.; Sun G.; and Wu E. 2019. Squeezeand-Excitation Networks. arXiv:1709.01507.  Hu J.; Shen L.; Albanie S.; Sun G.; and Wu E. 2019. Squeezeand-Excitation Networks. arXiv:1709.01507."},{"key":"e_1_3_2_1_28_1","volume-title":"2020 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), 1\u20136. IEEE.","author":"Kashihara K.","year":"2020","unstructured":"Kashihara , K. 2020 . Iris recognition for biometrics based on CNN with super-resolution GAN . In 2020 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), 1\u20136. IEEE. Kashihara, K. 2020. Iris recognition for biometrics based on CNN with super-resolution GAN. In 2020 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), 1\u20136. IEEE."},{"key":"e_1_3_2_1_29_1","unstructured":"Zhao H.; Gallo O.; Frosio I.; and Kautz J. 2015. Loss functions for neural networks for image processing. arXiv preprint arXiv:1511.08861.  Zhao H.; Gallo O.; Frosio I.; and Kautz J. 2015. Loss functions for neural networks for image processing. arXiv preprint arXiv:1511.08861."},{"volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 4690\u20134699","author":"Deng J.","key":"e_1_3_2_1_30_1","unstructured":"Deng , J. ; Guo , J. ; Xue , N. ; and Zafeiriou , S . 2019. Arcface: Additive angular margin loss for deep face recognition . In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 4690\u20134699 . Deng, J.; Guo, J.; Xue, N.; and Zafeiriou, S. 2019. Arcface: Additive angular margin loss for deep face recognition. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 4690\u20134699."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2015.09.002"},{"volume-title":"International Conference on Biometrics, 464\u2013471","author":"Wei Z.","key":"e_1_3_2_1_32_1","unstructured":"Wei , Z. ; Tan , T. ; Sun , Z. ; and Cui , J . 2006. Robust and fast assessment of iris image quality . In International Conference on Biometrics, 464\u2013471 . Springer. Wei, Z.; Tan, T.; Sun, Z.; and Cui, J. 2006. Robust and fast assessment of iris image quality. In International Conference on Biometrics, 464\u2013471. Springer."},{"volume-title":"2011 18th IEEE International Conference on Image Processing, 3117\u20133120","author":"Li X.","key":"e_1_3_2_1_33_1","unstructured":"Li , X. ; Sun , Z. ; and Tan , T . 2011. Comprehensive assessment of iris image quality . In 2011 18th IEEE International Conference on Image Processing, 3117\u20133120 . IEEE. Li, X.; Sun, Z.; and Tan, T. 2011. Comprehensive assessment of iris image quality. In 2011 18th IEEE International Conference on Image Processing, 3117\u20133120. IEEE."},{"key":"e_1_3_2_1_34_1","unstructured":"Paszke A.; Gross S.; Massa F.; Lerer A.; Bradbury J.; Chanan G.; Killeen T.; Lin Z.; Gimelshein N.; Antiga L.; 2019. Pytorch: An imperative style high-performance deep learning library. Advances in neural information processing systems 32:8026\u20138037  Paszke A.; Gross S.; Massa F.; Lerer A.; Bradbury J.; Chanan G.; Killeen T.; Lin Z.; Gimelshein N.; Antiga L.; 2019. Pytorch: An imperative style high-performance deep learning library. Advances in neural information processing systems 32:8026\u20138037"},{"key":"e_1_3_2_1_35_1","unstructured":"Chinese Academy of Sciences Institute of Automation CASIA iris image database http:\/\/biometrics.idealtest.org\/ 2014.  Chinese Academy of Sciences Institute of Automation CASIA iris image database http:\/\/biometrics.idealtest.org\/ 2014."}],"event":{"name":"IPMV 2022: 2022 4th International Conference on Image Processing and Machine Vision","acronym":"IPMV 2022","location":"Hong Kong China"},"container-title":["2022 4th International Conference on Image Processing and Machine Vision (IPMV)"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3529446.3529453","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3529446.3529453","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:31:25Z","timestamp":1750188685000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3529446.3529453"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,25]]},"references-count":35,"alternative-id":["10.1145\/3529446.3529453","10.1145\/3529446"],"URL":"https:\/\/doi.org\/10.1145\/3529446.3529453","relation":{},"subject":[],"published":{"date-parts":[[2022,3,25]]}}}